From the end of December through May, Chris Romero treks up remote mountain peaks in New Mexico. Shuree, near the northern end of the Valle Vidal, is one of his favorite spots.

“It’s about 20 miles back. You drive to the end of the road, then snow-machine in, and then ski in,” says Romero, a retired Air Force navigator who works as a snow survey hydrological technician for the U.S. Department of Agriculture’s Natural Resources Conservation Service.

These remote spots are important to the state's watersheds — and crucial for New Mexicans from all walks of life. Inhabitants of the state’s towns and cities, farmers and ranchers, and business communities all rely on a steady supply of water.

The snow measurements Romero and his fellow surveyors collect each year form the foundation for decisions water managers make each spring — decisions that divvy up water among cities, states, farmers and endangered species such as the Rio Grande silvery minnow. In the western United States, between 50 percent and 80 percent of the water cities and farmers depend upon comes from snowmelt.

And as bleak as southwestern springtime stream flow forecasts have been in recent years, scientists at the University of New Mexico are now saying that actually, they’re probably not bleak enough.

“The warm spring temperatures are one of the clearest observed climate change signals in North America,” says David Gutzler, a professor in the University of New Mexico Earth and Planetary Studies Department and one of the lead authors of the Intergovernmental Panel on Climate Change’s 2013 Assessment Report.

Those warming temperatures are affecting not just when and where snows fall, but how and when snowmelt finds its way — or doesn’t — into streams, rivers and reservoirs downstream. Put another way, the warming temperatures have made it more difficult to predict how much water will be available through the spring and summer — when water demands are greatest.

And that is forcing scientists and water managers to update the models they use to interpret measurements from surveyors like Romero.

Moving targets

Romero skis into the remote mountain areas the same time each month to collect snow data, using the same methods his predecessors used decades ago.

“If you like to be cold and wet and work really hard in the winter, it’s fun,” says Romero, who pulls a data notebook from a cabinet in his office in Albuquerque. A single sheet of paper is the prize at the end of each month’s quest. As soon as he’s down from the mountain, he copies the snow measurements and enters them online for forecasters in Colorado to read.

“If you lose it, all your work is gone and you have to go back,” he says.

Then, forecasters take over from there, analyzing the data collected from the mountaintops.

The forecasting program has been around since the mid-1930s and today, the Natural Resources Conservation Service collects data from more than 2,000 stations in 13 western states. Here in New Mexico, there are 27 automated SNOTEL — short for Snowpack Telemetry — stations and 24 active manual courses, like the ones Romero visits.

At the beginning of each month, between January and June, the NRCS releases stream flow forecasts. But predicting when and how quickly the snow will melt — and pour down the West’s streams and rivers — is a complicated process. It requires accurate snowfall data, historical records and cooperation with other agencies, like the National Weather Service.

Because of all those factors, forecasters don’t just say how much water will flow down the river channel. They offer a range of probabilities that can help people and water managers downstream plan for what might happen. Predicting water flow is like predicting the weather: It’s tricky because it’s a complex system involving many moving targets.

And although forecasters provide a range of probabilities, it has become apparent to folks like Gutzler that the NRCS has not adjusted enough for one of those moving targets — the climate’s continual warming.

Forecast overestimations

In 2014, the New Mexico Universities Working Group on Water Supply Vulnerabilities brought together scientists, engineers and economists from the state’s universities. Gutzler set aside some of that funding for his student, Shaleene Chavarria, to study the reliability of the stream flow forecasts.

By comparing several years’ worth of recent forecasts with the recorded stream flow, Chavarria found that the NRCS is consistently overestimating stream flow in New Mexico.

Gutzler says that overestimation is due in part to the region’s warmer and drier springs. Using past seasons as a guide, he says, the NRCS is estimating the spring and summer flows based on old patterns of snowmelt.

But as the southwestern United States continues to warm, snowpack will continue moving higher in elevation and further north. Those snows also melt earlier — and often, more quickly.

Even when there is a decent snowpack, when temperatures are warmer, less of that water makes it into rivers and reservoirs. Trees and other plants suck more moisture from the ground to survive, dry soils absorb the water instead of allowing it to flow downstream, and low humidity and dry winds whisk away the snow and ice, turning it into water vapor before it can melt into water.

Looking at the recent stream flow predictions for the Pecos River and the Rio Grande, Chavarria could see that the NRCS’s predictions were consistently too high — even when they were pretty measly.

“A warm, dry spring is death to snowpack,” says Gutzler. “The snow sublimates and doesn’t get into the river. So a low forecast turns into an abysmal forecast.”

Although forecasts become increasingly accurate through the spring as the chances for new snowfall decrease and the snowpack starts melting, they’re still based on what past years have been like, Chavarria explains, rather than accounting for current conditions, such as drought, higher spring temperatures or drier soil.

More research is necessary, Gutzler says, adding that other factors may contribute to low flows. But warming's effects on the state’s stream flows are undeniable. And as warming continues, it will have long-term impacts on streams, reservoirs and the state’s water supplies.

Their research isn’t meant to criticize the NRCS or its forecasters, says Gutzler. Rather, he and Chavarria view it as a step toward thinking about uncertainty and how to incorporate the changing climate’s realities into everything from forecasts to planning.

Tools at hand

The federal agency is already having conversations about climate change and how it is influencing forecasts.

Mike Stoebel, director of the NRCS’s National Water and Climate Center, says the use of 30-year records — currently, for the period 1980 through 2010 — remains critical. They enable analysts to compare past snowfalls with stream flows — and use those historical records as a basis for new estimates and forecasts.

“It’s just that there’s high variability with it,” he says.

That variability was obvious this year in Albuquerque.

This spring, snowpack in the Rio Grande Basin melted off early and very quickly. In early May, when the Rio Grande through Albuquerque should have still been high with snowmelt, it was low and slow. Then, just as water managers were worrying about reservoir levels and how they would make deliveries to farmers and provide water for the endangered Rio Grande silvery minnow, unexpected May rains hit — lasting through July — and bumped the river’s levels.

Built into forecasters’ analysis are unique weather patterns — such as El Niño — and current conditions, like temperatures and relative humidity. And soon they’ll glean even more information about soil moisture, which influences how much snowmelt will seep into the ground or run off into streams. About half the SNOTEL sites now have buried sensors that can measure soil temperature and moisture, says Stroebel.

Another factor that affects how quickly snowpack melts is the amount of dust that darkens snow. Increased dust can hasten melt off because darker colors absorb sunlight whereas lighter colors reflect it.

“As you can imagine, drier conditions during drought, as well as other factors like urbanization, land utilization by humans, and agriculture increase the dust levels in the snow and that in and of itself changes the albedo,” Stroebel says, referring to snow darkened with dust.

Not all of these factors can fit into the statistical model they use. That’s why the agency is incorporating new sources of information and working with additional partners and agencies that may be collecting different data or using alternative modeling programs, Stroebel says.

These days, there are larger extreme conditions — both warm and dry and cold and wet — and there is larger variability, and greater fluctuations in the 30-year period of record, Stroebel says.

“Like with most things, you do the best you can with the tools you have and the information you have on hand,” says Stroebel.